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package jdk.internal.random;

import java.util.concurrent.atomic.AtomicLong;
import java.util.random.RandomGenerator;
import jdk.internal.util.random.RandomSupport;
import jdk.internal.util.random.RandomSupport.AbstractSplittableWithBrineGenerator;

/**
 * A "splittable" pseudorandom number generator (PRNG) whose period
 * is roughly 2<sup>96</sup>.  Class {@link L32X64MixRandom} implements
 * interfaces {@link RandomGenerator} and {@link SplittableGenerator},
 * and therefore supports methods for producing pseudorandomly chosen
 * values of type {@code int}, {@code long}, {@code float}, {@code double},
 * and {@code boolean} (and for producing streams of pseudorandomly chosen
 * numbers of type {@code int}, {@code long}, and {@code double}),
 * as well as methods for creating new split-off {@link L32X64MixRandom}
 * objects or streams of such objects.
 *
 * <p>The {@link L32X64MixRandom} algorithm is a specific member of
 * the LXM family of algorithms for pseudorandom number generators;
 * for more information, see the documentation for package
 * {@link jdk.random}.  Each instance of {@link L32X64MixRandom}
 * has 96 bits of state plus one 32-bit instance-specific parameter.
 *
 * <p>If two instances of {@link L32X64MixRandom} are created with
 * the same seed within the same program execution, and the same
 * sequence of method calls is made for each, they will generate and
 * return identical sequences of values.
 *
 * <p>As with {@link java.util.SplittableRandom}, instances of
 * {@link L32X64MixRandom} are <em>not</em> thread-safe.  They are
 * designed to be split, not shared, across threads (see the {@link #split}
 * method). For example, a {@link java.util.concurrent.ForkJoinTask}
 * fork/join-style computation using random numbers might include a
 * construction of the form
 * {@code new Subtask(someL32X64MixRandom.split()).fork()}.
 *
 * <p>This class provides additional methods for generating random
 * streams, that employ the above techniques when used in
 * {@code stream.parallel()} mode.
 *
 * <p>Instances of {@link L32X64MixRandom} are not cryptographically
 * secure.  Consider instead using {@link java.security.SecureRandom}
 * in security-sensitive applications. Additionally,
 * default-constructed instances do not use a cryptographically random
 * seed unless the {@linkplain System#getProperty system property}
 * {@code java.util.secureRandomSeed} is set to {@code true}.
 *
 * @since   17
 *
 */
public final class L32X64MixRandom extends AbstractSplittableWithBrineGenerator {
    /*
     * Implementation Overview.
     *
     * The split operation uses the current generator to choose four new 32-bit
     * int values that are then used to initialize the parameter `a` and the
     * state variables `s`, `x0`, and `x1` for a newly constructed generator.
     *
     * With high probability, no two generators so chosen will have the same
     * `a` parameter, and testing has indicated that the values generated by
     * two instances of {@link L32X64MixRandom} will be (approximately)
     * independent if the two instances have different values for `a`.
     *
     * The default (no-argument) constructor, in essence, uses
     * "defaultGen" to generate four new 32-bit values for the same
     * purpose.  Multiple generators created in this way will certainly
     * differ in their `a` parameters.  The defaultGen state must be accessed
     * in a thread-safe manner, so we use an AtomicLong to represent
     * this state.  To bootstrap the defaultGen, we start off using a
     * seed based on current time unless the
     * java.util.secureRandomSeed property is set. This serves as a
     * slimmed-down (and insecure) variant of SecureRandom that also
     * avoids stalls that may occur when using /dev/random.
     *
     * File organization: First static fields, then instance
     * fields, then constructors, then instance methods.
     */

    /* ---------------- static fields ---------------- */

    /**
     * The seed generator for default constructors.
     */
    private static final AtomicLong defaultGen = new AtomicLong(RandomSupport.initialSeed());

    /*
     * Multiplier used in the LCG portion of the algorithm.
     * Chosen based on research by Sebastiano Vigna and Guy Steele (2019).
     * The spectral scores for dimensions 2 through 8 for the multiplier 0xadb4a92d
     * are [0.975884, 0.936244, 0.755793, 0.877642, 0.751300, 0.789333, 0.728869].
     */

    private static final int M = 0xadb4a92d;

    /* ---------------- instance fields ---------------- */

    /**
     * The parameter that is used as an additive constant for the LCG.
     * Must be odd.
     */
    private final int a;

    /**
     * The per-instance state: s for the LCG; x0 and x1 for the XBG.
     * At least one of x0 and x1 must be nonzero.
     */
    private int s, x0, x1;

    /* ---------------- constructors ---------------- */

    /**
     * Basic constructor that initializes all fields from parameters.
     * It then adjusts the field values if necessary to ensure that
     * all constraints on the values of fields are met.
     *
     * @param a additive parameter for the LCG
     * @param s initial state for the LCG
     * @param x0 first word of the initial state for the XBG
     * @param x1 second word of the initial state for the XBG
     */
    public L32X64MixRandom(int a, int s, int x0, int x1) {
        // Force a to be odd.
        this.a = a | 1;
        this.s = s;
        this.x0 = x0;
        this.x1 = x1;
        // If x0 and x1 are both zero, we must choose nonzero values.
        if ((x0 | x1) == 0) {
       int v = s;
            // At least one of the two values generated here will be nonzero.
            this.x0 = RandomSupport.mixMurmur32(v += RandomSupport.GOLDEN_RATIO_32);
            this.x1 = RandomSupport.mixMurmur32(v + RandomSupport.GOLDEN_RATIO_32);
        }
    }

    /**
     * Creates a new instance of {@link L32X64MixRandom} using the
     * specified {@code long} value as the initial seed. Instances of
     * {@link L32X64MixRandom} created with the same seed in the same
     * program generate identical sequences of values.
     *
     * @param seed the initial seed
     */
    public L32X64MixRandom(long seed) {
        // Using a value with irregularly spaced 1-bits to xor the seed
        // argument tends to improve "pedestrian" seeds such as 0 or
        // other small integers.  We may as well use SILVER_RATIO_64.
        //
        // The high half of the seed is hashed by mixMurmur32 to produce the `a` parameter.
        // The low half of the seed is hashed by mixLea32 to produce the initial `x0`,
        // which will then be used to produce the first generated value.
        // Then x1 is filled in as if by a SplitMix PRNG with
        // GOLDEN_RATIO_32 as the gamma value and mixLea32 as the mixer.
        this(RandomSupport.mixMurmur32((int)((seed ^= RandomSupport.SILVER_RATIO_64) >>> 32)),
             1,
             RandomSupport.mixLea32((int)(seed)),
             RandomSupport.mixLea32((int)(seed) + RandomSupport.GOLDEN_RATIO_32));
    }

    /**
     * Creates a new instance of {@link L32X64MixRandom} that is likely to
     * generate sequences of values that are statistically independent
     * of those of any other instances in the current program execution,
     * but may, and typically does, vary across program invocations.
     */
    public L32X64MixRandom() {
        // Using GOLDEN_RATIO_64 here gives us a good Weyl sequence of values.
        this(defaultGen.getAndAdd(RandomSupport.GOLDEN_RATIO_64));
    }

    /**
     * Creates a new instance of {@link L32X64MixRandom} using the specified array of
     * initial seed bytes. Instances of {@link L32X64MixRandom} created with the same
     * seed array in the same program execution generate identical sequences of values.
     *
     * @param seed the initial seed
     */
    public L32X64MixRandom(byte[] seed) {
        // Convert the seed to 4 int values, of which the last 2 are not all zero.
        int[] data = RandomSupport.convertSeedBytesToInts(seed, 4, 2);
        int a = data[0], s = data[1], x0 = data[2], x1 = data[3];
        // Force a to be odd.
        this.a = a | 1;
        this.s = s;
        this.x0 = x0;
        this.x1 = x1;
    }

    /* ---------------- public methods ---------------- */

    @Override
    public SplittableGenerator split(SplittableGenerator source, long brine) {
       // Pick a new instance "at random", but use (the low 31 bits of) the brine for `a`.
        return new L32X64MixRandom((int)brine << 1, source.nextInt(),
                   source.nextInt(), source.nextInt());
    }

    @Override
    public int nextInt() {
       // Compute the result based on current state information
       // (this allows the computation to be overlapped with state update).
        final int result = RandomSupport.mixLea32(s + x0);

       // Update the LCG subgenerator
        s = M * s + a;

       // Update the XBG subgenerator
        int q0 = x0, q1 = x1;
        {   // xoroshiro64
            q1 ^= q0;
            q0 = Integer.rotateLeft(q0, 26);
            q0 = q0 ^ q1 ^ (q1 << 9);
            q1 = Integer.rotateLeft(q1, 13);
        }
        x0 = q0; x1 = q1;

        return result;
    }

    @Override
    public long nextLong() {
        return ((long)nextInt() << 32) ^ (long)nextInt();
    }

}
